Localized Image Retrieval Based on Interest Points

Colour Interest Points for Image Retrieval

In image retrieval scenarios, many methods use interest point detection at an early stage to find regions in which descriptors are calculated. Finding salient locations in image data is crucial for these tasks. Observing that most current methods use only the luminance information of the images, we investigate the use of colour information in interest point detection. Based on the Harris corner...

Content Based Image Retrieval Using Interest Points and Texture Features

Content Based Image Retrieval Using Interest Points and Texture Features

Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. In this work we present methods for content based image retrieval based on texture similarity using interest points and Gabor features. Interest point detectors are used in computer vision to detect image points with special properties, which can be geometric (corn...

Image Retrieval Based on Regions of Interest

Query-by-example is the most popular query model in recent contentbased image retrieval (CBIR) systems. A typical query image includes relevant objects (e.g., Eiffel Tower), but also irrelevant image areas (including background). The irrelevant areas limit the effectiveness of existing CBIR systems. To overcome this limitation, the system must be able to determine similarity based on relevant r...

Image Retrieval Based on Region of Interest

Content Based Image Retrieval (CBIR) is browsing, searching and navigation of images from large image databases based on their visual content. CBIR has been an active area of research for more than a decade. Many CBIR systems have been developed; like QBIC [Flickner et al. (1995)], Simplicity [Wang et al. (2001)], and Blob world [Carson et al.(2002)]. A detailed survey of CBIR techniques can be...